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arXiv · 2407.07735

Protecting NeRFs' Copyright via Plug-And-Play Watermarking Base Model

Qi Song·Ziyuan Luo·Ka Chun Cheung·Simon See·Renjie Wan
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Abstract

Neural Radiance Fields (NeRFs) have become a key method for 3D scene representation. With the rising prominence and influence of NeRF, safeguarding its intellectual property has become increasingly important. In this paper, we propose \textbf{NeRFProtector}, which adopts a plug-and-play strategy to protect NeRF's copyright during its creation. NeRFProtector utilizes a pre-trained watermarking base model, enabling NeRF creators to embed binary messages directly while creating their NeRF. Our plug-and-play property ensures NeRF creators can flexibly choose NeRF variants without excessive modifications. Leveraging our newly designed progressive distillation, we demonstrate performance on par with several leading-edge neural rendering methods. Our project is available at: \url{https://qsong2001.github.io/NeRFProtector}.

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Qi Song, Ziyuan Luo, Ka Chun Cheung, Simon See, Renjie Wan. 2024-07-10. Protecting NeRFs' Copyright via Plug-And-Play Watermarking Base Model. https://arxiv.org/abs/2407.07735

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